Semantic segmentation of the multiform proximal femur and femoral head bones with the deep convolutional neural networks in low quality MRI sections acquired in …
Medical image segmentation is one of the most crucial issues in medical image processing
and analysis. In general, segmentation of the various structures in medical images is …
and analysis. In general, segmentation of the various structures in medical images is …
A novel approach for computerized quantitative image analysis of proximal femur bone shape deformities based on the hip joint symmetry
As a result of most of the bone disorders seen in hip joints, shape deformities occur in the
structural form of the hip joint components. Image-based quantitative analysis and …
structural form of the hip joint components. Image-based quantitative analysis and …
Fast and accurate registration of the proximal femurs in bilateral hip joint images by using the random sub-sample points
Abstract Background and Objective As is known, point clouds representing the objects are
frequently used in object registration. Although the objects can be registered by using all the …
frequently used in object registration. Although the objects can be registered by using all the …
Image based quantification of the proximal femur shape deformities in 3D by using the contralateral healthy shape structure: A preliminary study
As a result of the several hip joint disorders seen on the hip joint components, shape
deformities occur in the morphological structure of the proximal femurs and femoral heads …
deformities occur in the morphological structure of the proximal femurs and femoral heads …
Automatic classification of the waldenstrom stages of Legg-Calve-Perthes disease from the 2D total proximal femur shape deformity
By various hip joint disorders, human proximal femurs are deformed and the natural pure
shape of the human proximal femurs is lost. Automatic classification of the proximal femur …
shape of the human proximal femurs is lost. Automatic classification of the proximal femur …